cerebras vs groq — AI API latency comparison

Last verified September 07, 2026

As of September 07, 2026, cerebras has lower edge latency (time-to-first-byte) than groq in 3 of 4 measured region(s). From Europe (Germany), cerebras responds in 200 ms p50 vs 296 ms.

Is cerebras or groq faster in each region?

Full details: cerebras by region · groq by region.

Does the answer change by region?

The answer flips depending on where you measure from. In Europe (Germany) the gap is widest at 97 ms, while in South America (São Paulo) it narrows to 49 ms — and the faster provider is not the same one in every region.

This is why a single-location benchmark cannot answer “is cerebras or groq faster” for you. Pick the row that matches where your requests originate.

Does cerebras or groq have better uptime?

Over the last 24 hours cerebras and groq are level on availability at 100% of probes succeeding across 4 region(s). Neither is separated from the other by uptime at this sample size.

Availability observed by our probes over the last 24 hours, not a contractual SLA. Providers publish their own SLA terms and their own status pages; this is an outside view of whether requests actually completed, which is the number a status page cannot give you about your own region. The worst region is shown next to the average because an average hides the one place where a share of your users sees a different service. Longer windows and all 4 regions: uptime comparison · confirmed outages: incidents.

What exactly is being compared?

Both providers are measured the same way, from the same probes, on the same schedule: a real connection is opened to each provider’s own API host and DNS, TCP, TLS and the first response byte are timed. Neither is measured through a gateway or aggregator, so the numbers reflect each provider’s own infrastructure. Figures are p50 and p95 over the last 24 hours; percentiles are nearest-rank, because a handful of outliers would distort an average.

What this comparison does not cover

This is edge latency — the time before the model starts working. It is the floor you pay on every request regardless of which model you call, and it is the part you cannot optimise away with a better prompt. It is not time-to-first-token, throughput, price or answer quality: those depend on the specific model, and comparing them across providers running different models would not be like-for-like. Measured time to first token (TTFT), with the model named next to every figure and the network share broken out, is on the time to first token page.

Method in full: methodology · Raw numbers under CC BY 4.0: JSON API · No provider pays for placement.